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Business-as-unusual: Exploring port stakeholders’ time tactics for mediating recent disruptions at the Port of Rotterdam
No full textSeaports function as infrastructural nodes at which the disparate rhythms of global logistical flows are synchronized toward just-in-time management. Port disruptions challenge this regular time regime. This article explores the role of infrastructures and time tactics in mediating port disruptions associated with the COVID-19 pandemic and the war in Ukraine. Building on three interrelated notions of time—infrastructural time regimes, infrastructural rhythms, and infrastructural time tactics—our analysis of stakeholder interviews revealed that to manage port disruptions, port stakeholders applied various time tactics to certain processes: activating or deactivating, prioritizing or downgrading, continuing or discontinuing, and increasing or decreasing. By employing these time tactics to maintain, adapt, and transform port rhythms in response to disruptions, port stakeholders attempted to resynchronize disrupted port rhythms into a different time regime. We demonstrate that this time regime is “hybrid,” as it comprises not only elements of just-in-time management but also elements of just-in-case management. This finding introduces a more nuanced understanding of the temporary hybridization of time regimes during periods of disruptions and highlights the role of infrastructures in mediating time
Automated Batch Processing of Diurnal Cardiac Activity: Comparison of Fully Automated Batch- to Gold-Standard Manual Processing
No full textThe analysis of long-term variation patterns in heart rate (HR) and heart rate variability (HRV) provides insights into autonomic nervous system function beyond short-term recordings taken under resting or experimental conditions. Yet, traditional processing pipelines often require time- and labor-intensive visual inspection of electrocardiography (ECG) data and manual artifact removal. This study evaluated the performance of 3 code-based fully automated batch-processing pipelines—NeuroKit2, RHRV, and Systole—against the manual gold standard utilizing Kubios for both (diurnal) HR and HRV estimates derived from raw 48-h ECG recordings. Results illustrate that while automated pipelines yield HR estimates in good agreement to the gold standard (r = 0.91-0.99; α = 0.90-0.99), HRV estimates exhibit greater deviations (r = 0.66-0.87; α = 0.76-0.90). Cosinor analyses of diurnal HR patterns indicate strong consistency between Kubios and NeuroKit2 (r = 0.94-0.99; α = 0.97-0.99), but weaker correlations with RHRV and Systole (r = 0.58-0.87; α = 0.63-0.93). HRV cosinor parameters showed even larger discrepancies, with parameter-dependent correlations ranging from r = 0.41 to 0.86 and Cronbach’s alphas from α = 0.59 to 0.91. Findings suggest that automated batch processing of ECG data for analyzing diurnal variation patterns in HR and HRV produces results that show moderate to good agreement with the gold standard including visual inspection and manual processing. However, caution is warranted, as existing toolboxes and pipelines may lead to different results
Contestations of Liberal Globalism and the Rise of the Retrograde Party
No full textThe crisis of the liberal order opened up space for ideas that only some years ago had appeared out of time. During globalization’s heyday, parties that called for a rollback of liberal globalism were either stuck in a marginal position or unable to implement fundamental reforms. This has changed as the main political approaches toward liberal globalism are now being publicly and electorally contested. We argue that this has triggered the rise of a phenomenon we refer to as retrogradism. This article applies the concept of retrogradism to the case of the German right-wing party Alternative für Deutschland (AfD). It argues that we may be witnessing the rise of a new type of political party that pursues a retrograde agenda. We suggest that the current debate on the AfD fails to take into account that its defining features may be its politics of time and its retrograde opposition to liberal globalism
Toward quantification of the information content in flow variables under cycle-to-cycle variations
No full textCycle-to-cycle variations (CCV) pose significant challenges to the performance and reliability of internal combustion engines (ICE). This study investigates the applicability of information entropy as a diagnostic tool to quantify and characterize CCV in ICE subject to exhaust gas recirculation (EGR). Particle image velocimetry (PIV) and flame imaging were used to measure the flow field and flame behavior. The concept of information entropy is related to flow and flame evolution by calculating the Shannon entropy of the turbulent kinetic energy and flow velocity components to assess their sensitivity to CCV. Shannon entropy was applied to the flow velocity components and the turbulent kinetic energy on the tumble plane, where the horizontal component was identified to correlate with high-speed (HC) and low-speed (LC) combustion cycles both, with and without EGR. The turbulent kinetic energy was found to be major driver of HC cycles without EGR, however, it plays a subordinate role with EGR. The conditional Shannon entropy was then applied to assess local fluctuation of the turbulent kinetic energy during ignition from cycle-to-cycle under the influence of the direction of the horizontal velocity component and the presence or absence of the flame, revealing the areas where turbulent kinetic energy fluctuates strongly between different cycles. The results have potential for both computational and experimental studies of ICE, since the use of information entropy as a diagnostic tool allows for early prediction of HC and LC cycles
Sequential maximum-likelihood estimation of wideband polynomial-phase signals on sensor array
No full textThis paper presents a novel sequential estimator for the direction-of-arrival and polynomial coefficients of wideband polynomial-phase signals impinging on a sensor array. Addressing the computational challenges of maximum-likelihood estimation for this problem, we propose a method leveraging random sampling consensus (RANSAC) applied to the time-frequency spatial signatures of sources. Our approach supports multiple sources and higher-order polynomials by employing coherent array processing and sequential approximations of the maximum-likelihood cost function. We also propose a low-complexity variant that estimates source directions via angular domain random sampling. Numerical evaluations demonstrate that the proposed methods achieve Cramér-Rao bounds in challenging multi-source scenarios, including closely spaced time-frequency spatial signatures, highlighting their suitability for advanced radar signal processing applications
Critical nanoparticle formation in iron combustion: single particle experiments with in-situ multi-parameter diagnostics aided by multi-scale simulations
No full textIn practical iron combustion systems, the formation of iron oxide nanoparticles (NP) presents challenges such as efficiency penalties and fine dust emissions, necessitating a deeper understanding of the underlying formation mechanisms and critical thermochemical conditions. This study, utilizing both experiments and multi-scale simulation tools, investigates the NP clouds generated by single iron particles burning in high-temperature oxidizing environments. The ambient gas conditions were provided by a laminar flat flame burner, where the post-flame oxygen mole fraction was varied between 20, 30, and 40 vol%, with a constant gas temperature of approximately 1800 K. In the experiments, high-speed in-situ diagnostics were employed to simultaneously measure particle size, NP release onset, NP cloud evolution, and the surface temperature history of the microparticles. The setup involved three 10 kHz imaging systems: one for two-color pyrometry and two for diffuse backlight-illumination (DBI), specifically targeting microparticle size and nanoparticle cloud measurements. The study demonstrates the powerful capabilities of these multi-physics diagnostics, allowing for precise quantification of NP release onset time and temperature, which were found to depend on both particle size and ambient oxygen mole fractions. Detailed CFD simulations revealed that the enhanced convection velocity, driven by increased Stefan flow, transports NPs towards the parent iron particles, particularly under high-oxygen conditions. This phenomenon delayed the appearance of detectable NP clouds, leading to higher apparent microparticle temperatures at the onset of NP release. This insight complemented the experimental observations, providing a more comprehensive understanding of the observed NP-cloud release temperature that increases with higher oxygen levels. Further analysis through molecular dynamics (MD) simulations uncovered potential reaction pathways of precursor formation and nanoparticle agglomeration. The MD simulations showed that the initial temperature significantly influenced the amount of gas-phase precursors and subsequently the composition of the resulting nanoclusters, with Fe(II) predominating at higher temperatures and Fe(III) at lower temperatures. This integrated approach combining experiments and numerical analysis not only advances our understanding of NP formation in iron combustion but also provides valuable insights into the thermochemical conditions that dominate nanoparticle characteristics
Correlating spatially resolved catalysis and Raman spectroscopy during CO oxidation over Cu/CeO₂ catalysts
No full textSpatially resolved analysis allows for the development of accurate structure–property correlations in regimes of high catalytic conversion. We report on the novel combination of a compact profile reactor with IR spectroscopy for spatially resolved gas-phase analysis and with Raman spectroscopy for spatially resolved structural analysis. The potential of this combined approach is illustrated for the CO oxidation over low-loaded Cu/CeO₂ catalysts at atmospheric pressure but the use of higher pressures is feasible. Spatially resolved operando Raman spectroscopy of Cu/CeO₂ at 150 °C reveals structural changes directly correlated with the catalytic conversion. With increasing conversion an increase in the consumption of surface lattice oxygen is observed which is accompanied by the formation of oxygen vacancies and ceria reduction. Our mechanistic findings demonstrate the participation of the ceria support in the CO oxidation over low-loaded Cu/CeO₂ catalysts at high conversions. The presented setup provides high versatility for spatially dependent mechanistic analysis of catalysts as a function of varying gas environments and their influence on the structural changes
How Well-being in the Digital Workplace Shapes Employee Experience: A Socio-Technical Study on Loyalty and Performance
No full textContext Is Cue-Cial: Assessing the Interpretation of Social Signals from Non-anthropomorphic Robots in Different Contexts
No full textHumans excel at understanding social cues in communication, but robots struggle. Social cues are crucial for humans to interpret the intentions of their communication partners. Research indicates that we typically interpret the actions of anthropomorphic robots analogously to their human counterparts, paving a clear path to the design of appropriate social cues. For non-anthropomorphic robots, however, it is an open question how humans interpret social cues with different output modalities and in different contexts. Our study investigates whether social cues signaled by typical non-anthropomorphic modalities such as lights, sounds, and gestures are consistently interpreted across people and contexts. We, therefore, conducted a contextual investigation in a hospital, derived scenarios from co-design workshop, and tested 103 cues collected from the literature in a large online survey (N = 1545). Our results demonstrate that most human interpretations vary by context, highlighting the need to design dynamic and adaptive social cues for interactive robotic systems
Dense dislocations and coarse grains enable high thermoelectric performance of Mg3(Sb, Bi)2-based alloys
No full textGrain boundary and defect engineering plays a crucial role in the manipulation of thermoelectric performance. For Mg3(Sb, Bi)2 alloys, it still remains a challenge to simultaneously realize coarse grains and dense dislocations. Herein, we demonstrate that minor Cu doping can significantly increase grain size and improve carrier mobility in n-type Mg3.2CuxSbBi0.97Te0.03 (0 ≤ x ≤ 0.05) samples. The carrier scattering mechanism is manipulated from mixed scattering to acoustic phonon dominated scattering. This results in a high electrical conductivity of 850 S cm-1 at room temperature for the x = 0.025 sample, an improvement of about 70% compared to the matrix, without any reduction in the Seebeck coefficient. Thus, an outstanding power factor of ∼ 25.4 μW cm-1 K-2 at 473 K is achieved. Meanwhile, the interstitial Cu atoms induce lattice distortions, and a high-density dislocation network is observed by the HRTEM in the Cu-doped samples, which effectively suppresses phonon transport, resulting in a low lattice thermal conductivity of ∼ 0.48 W m-1 K-1 at 623 K. The synergistic effects of coarse grains and dense dislocations enable an excellent zT of 1.73 (723 K) and zTave of 1.35 (300 K-723 K). In addition, the Cu-doped samples exhibit excellent mechanical properties with a significant plastic deformation of ∼ 40% and a high compressive stress of ∼ 519 MPa. This work paves the way for synergistically optimizing the electron and phonon transport in Mg3(Sb, Bi)2-based alloys